# US 12,762,701 B2 · Method and device for setting the visibility of objects in a projection image generated by radiation

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- Number: US 12,762,701 B2
- Document ID: US12762701B2
- Status: Granted
- Kind: B2
- Application number: 18/757,314
- Filed: 2024-06-27
- Published: 2025-01-09
- Granted: 2026-10-13
- Earliest claimed: 2023-07-05
- Assignees: Ziehm Imaging GmbH
- Applicants: Ziehm Imaging GmbH
- Inventors: Tim Vöth; Thomas König; Klaus Hörndler; Michael Knaup; Marc Kachelriess
- Web page: https://patentgrep.com/patent/US12762701B2

## CPC

- G06T 7/0012: {Biomedical image inspection}
- G06T 5/50: using two or more images, e.g. averaging or subtraction
- G06T 15/00: Three-dimensional [3D] image rendering
- G06V 10/764: using classification, e.g. of video objects
- G16H 30/40: for processing medical images, e.g. editing
- G06T 2207/10116: X-ray image
- G06T 2207/20081: Training; Learning
- G06T 2207/20221: Image fusion; Image merging
- G06T 2207/30024: Cell structures in vitro; Tissue sections in vitro
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

A method for setting the visibility of objects in a projection image generated by radiation of an anatomical region includes loading imaging data representing a projection image generated by radiation into a memory of a computer, generating a first partial image from the imaging data using a first semantic class by an artificial intelligence device executing an artificial intelligence algorithm, combining the first partial image and the imaging data to generate an output image using a first adjustable function with at least one first parameter such that the first function determines a rendering of the first partial image in the output image, displaying an output image on a display device; and generating training data for training the artificial intelligence algorithm of the artificial intelligence device.

## Claims

### Claim 1

A method for setting the visibility of objects in a projection image generated by radiation of an anatomical region, the method comprising:
loading imaging data representing a projection image generated by radiation into a memory of a computer;
generating a first partial image from the imaging data, using a first semantic class by an artificial intelligence device executing an artificial intelligence algorithm, wherein the first semantic class includes at least one of the following semantic classes: a representation of an image of an anatomical structure, a representation of an image of a medical implant, a representation of an image of a medical instrument, and a representation of an image of a medical fastening element;
combining the first partial image and the imaging data to generate an output image using a first adjustable function with at least one first parameter, wherein the first adjustable function determines a rendering of the first partial image in the output image, and wherein the at least one first parameter is selected by at least one of the following: at least one user input, a type of anatomical region to be examined, the first semantic class, or the type of medical procedure;
displaying an output image on a display device; and
generating training data for training the artificial intelligence algorithm of the artificial intelligence device by at least:
generating the training data for training the artificial intelligence algorithm of the artificial intelligence device from at least one set of an input image and a first target image; and
generating the first target image by:
replacing, in a region of a first three-dimensional image model of the patient's tissue from which the input image is generated, imaging data representing the first semantic class with imaging data representing the surrounding tissue, to generate a second three-dimensional image model; and
generating at least one first target image based at least in part on an image generated from the second three-dimensional image model;
wherein each input image corresponds to a projection image of the anatomical region to be examined, which is generated by radiation or the generation of which by radiation is partially or completely simulated; and
wherein at least one first target image has imaging information of the first semantic class.

### Claim 2 (depends on 1)

The method of claim 1, wherein the rendering of the first partial image in the output image comprises at least a visibility, a brightness, a contrast, or a color of the first partial image in the output image.

### Claim 3 (depends on 1)

The method of claim 1, wherein generating the training data for the artificial intelligence algorithm of the artificial intelligence device is performed on an artificial intelligence training device.

### Claim 4 (depends on 1)

The method of claim 1, wherein each input image comprises imaging information of the first semantic class.

### Claim 5 (depends on 1)

The method of claim 1, further comprising:
generating a second partial image from the imaging data, using a second semantic class by an artificial intelligence device executing an artificial intelligence algorithm, wherein the second semantic class includes at least one of the following semantic classes: a representation of an image of an anatomical structure, a representation of an image of a medical implant, a representation of an image of a medical instrument, and a representation of an image of a medical fastening element; and
combining the first partial image, the second partial image and the imaging data to generate the output image using a function with the first adjustable function with the at least one first parameter and with a second adjustable function with at least one second parameter, wherein the second function determines the rendering of the second partial image in the output image, and wherein the at least one second parameter is selected by at least one of the following: at least one user input, the type of anatomical region to be examined, the second semantic class, or the type of medical procedure.

### Claim 6 (depends on 5)

The method of claim 5, further comprising:
generating an nth partial image from the imaging data, using an nth semantic class by the artificial intelligence device executing an artificial intelligence algorithm, wherein the nth semantic class includes at least one of the following semantic classes: a representation of an image of an anatomical structure, a representation of an image of a medical implant, a representation of an image of a medical instrument, and a representation of an image of a medical fastening element; and
combining the partial images 1 to n with the imaging data to generate the output image using a function with n adjustable functions each with at least one parameter, wherein the first to nth function determines the rendering of the first to nth partial image in the output image, and wherein the respective at least one parameter is selected by at least one of the following: at least one user input, the type of anatomical region, the nth semantic class, or the type of medical procedure.

### Claim 7 (depends on 1)

The method of claim 1, wherein the input image is generated from a three-dimensional image model of a patient's tissue.

### Claim 8 (depends on 1)

The method of claim 1, wherein generating the first target image comprises:
selecting a semantic class as a selected class, the imaging information of which is to be retained in the first target image;
loading the first three-dimensional image model of a patient's tissue into the memory of the computer, wherein the first three-dimensional image model of the patient's tissue comprises three-dimensional imaging information of the selected semantic class;
generating the second three-dimensional image model, which does not comprise imaging information of the selected semantic class by replacing, in a region of the first three-dimensional image model of the patient's tissue, imaging information representing the selected semantic class with imaging information representing the surrounding tissue;
generating the input image from the first three-dimensional image model of the patient's tissue;
generating at least one intermediate image from the second three-dimensional image model; and
generating the at least one first target image by subtracting the intermediate image from the input image.

### Claim 9 (depends on 8)

The method of claim 8, wherein:
the three-dimensional image model of the patient's tissue is generated by using three-dimensional X-ray imaging; or
the three-dimensional image model of the patient's tissue is generated from a simulation of three-dimensional X-ray imaging.

### Claim 10 (depends on 8)

The method of claim 8, wherein:
the three-dimensional imaging information of the selected semantic class is generated by using three-dimensional X-ray imaging; or
the three-dimensional imaging information of the selected semantic class is generated from a simulation of three-dimensional X-ray imaging.

### Claim 11 (depends on 1)

The method of claim 1, further comprising:
setting the first parameter by a first operating device;
setting the second parameter by a second operating device; or
setting at least one nth parameter by at least one nth operating device.

### Claim 12 (depends on 1)

The method of claim 1, wherein the first parameter is a weighting factor.

### Claim 13 (depends on 5)

The method of claim 5, wherein the output image is generated as a sum of:
the projection image generated by radiation;
the first parameter multiplied by the first partial image; and
the second parameter multiplied by the second partial image.

### Claim 14 (depends on 5)

The method of claim 5, wherein the at least one set comprises a second target image comprising imaging information of the second semantic class.

### Claim 15

A medical imaging device comprising:
a radiation source configured to emit radiation and a radiation sensor upon which the radiation is incident after passing through an anatomical tissue, wherein the radiation sensor is configured to output radiation data;
a projection image generating device configured to generate a projection image from the radiation data;
a memory configured to store imaging data representing the projection image generated by radiation;
an artificial intelligence device configured to generate a first partial image from the imaging data using a first semantic class by means of an artificial intelligence algorithm, wherein the first semantic class includes at least one of the following semantic classes: a representation of an image of an anatomical structure, a representation of an image of a medical implant, a representation of an image of a medical instrument, and a representation of an image of a medical fastening element;
a combination device configured to combine the first partial image and the imaging data to generate an output image using a first adjustable function with at least one first parameter, wherein the at least one first parameter is selected by at least one of the following: at least one user input, a type of anatomical region to be examined, the first semantic class, or a type of medical procedure;
a display device configured to display the output image; and
an artificial intelligence training device configured for:
generating training data for training the artificial intelligence algorithm of the artificial intelligence device based on at least one set of an input image and a first target image; and
generating the first target image by:
replacing, in a region of a first three-dimensional image model of the patient's tissue from which the input image is generated, imaging data representing the first semantic class with imaging data representing the surrounding tissue, to generate a second three-dimensional image model; and
generating at least one first target image based at least in part on an image generated from the second three-dimensional model;
wherein each input image corresponds to a projection image of the anatomical region to be examined, which is generated by radiation or the generation of which by radiation is partially or completely simulated; and
wherein at least one first target image has imaging information of the first semantic class.